Exploring condensable organic vapors and their co-occurrence with PM_2.5 and O₃ in winter in Eastern China

Abstract

Oxygenated organic molecules (OOMs) are important oxidation products of volatile organic compounds (VOCs), and they act as key condensable vapors for new particle formation (NPF) and secondary organic aerosol (SOA) in the atmosphere. However, the large diversity and extremely low concentration make OOMs unmeasurable by conventional means, resulting in a poor understanding of OOMs, especially their formation. Herein, we observed OOMs with state-of-the-art mass spectrometry in a megacity in eastern China during the winter and characterized them by performing positive matrix factorization on binned mass spectra (binPMF). The binPMF analysis revealed 3 factors with clear precursor profiles (1 aromatic and 2 aliphatics), 2 ozone-related factors, 2 mixed-precursor-derived factors with unclear processes, and 4 factors dominated by nitrated phenols. We performed peak assignment on binPMF factors and identified over 1500 molecules with a mean total concentration of 4.7 × 10⁷ molecules per cm³ with all nitrated phenols excluded. Most OOMs are organic nitrates produced by the oxidation of anthropogenic VOC with interactions between the derived RO₂ and NO_x. These molecules containing 3 to 7 effective oxygen atoms (excluding –NO₂ in the nitrate moiety) introduced by autoxidation and multigenerational oxidation are less volatile, and hence, are susceptible to condensational loss. However, the observed OOM concentrations increase with the buildup of PM_2.5. This can be explained by enhanced OOM photochemical production owing to accumulated VOCs and sustained oxidants that outcompete condensational loss. This suggests favored SOA production via OOM condensation during haze. Furthermore, the highest OOM concentrations occur when PM_2.5 and O₃ are coenhanced. Under this condition, OOMs mainly come from ozone-related factors that are generated jointly with ozone and from aliphatic-dominated factors that are closely associated with PM_2.5. Overall, our results improve the understanding of OOM formation and its impact on the polluted atmosphere.

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Environmental significance

Atmospheric secondary organic aerosols, whose precursors are volatile organic compounds, significantly affect climate forcing and human health. The discovery of oxygenated organic molecules (OOMs), which act as crucial intermediates, provides an opportunity to understand organic gas oxidation and aerosol formation at the molecular level. However, comprehensive elucidation of the nature and formation of OOMs is far from achieved, particularly in densely populated areas suffering from severe air pollution. Herein, we investigated wintertime OOMs observed using advanced mass spectrometry in a typical urban environment. We found that OOMs are produced from anthropogenic organic gas oxidation and interacted strongly with nitrogen oxides. Importantly, the photochemical production of OOMs and their corresponding contributions to aerosol are amplified during haze. Some characteristic OOM formation processes are linked to the simultaneous enhancement of PM_2.5 and ozone.

1 Introduction

Secondary organic aerosol (SOA) is a ubiquitous and important component of atmospheric submicron particles,¹ which deteriorate air quality,^2,3 endanger human health⁴ and affect the earth's radiation balance.⁵ The oxidation of volatile organic compounds (VOCs) from anthropogenic and biogenic emissions ultimately leads to the formation of SOA,^6,7 with oxygenated organic molecules (OOMs)^8–10 being key intermediates in this convoluted process. Unlike traditional oxygenated VOCs, OOMs discovered using the latest developed mass spectrometric techniques^11–13 are a subset of VOC oxidation products attaining multiple oxygenated functionalities; thus, they are considerably less volatile than their precursors. Generally, OOMs belonging to ultra-low-volatility VOC (ULVOC) can participate in particle nucleation (∼1 nm);^14,15 OOMs belonging to extremely-low-volatility (ELVOC) can drive the initial growth (1–3 nm);¹⁶ and OOMs belonging to low-volatility VOC (LVOC) dominate the subsequent growth (3 to >50 nm).⁸ When particles contain organic components, OOMs belonging to semi-volatile VOC (SVOC) can partition into the particle phase. All these processes are responsible for SOA formation.^17,18

Currently, the formation of OOMs remains elusive.⁹ Conventional VOC oxidation mechanisms¹⁹ cannot account for OOMs with high O/C ratios. New ideas, including the autoxidation of organic peroxy radicals (RO₂),^20,21 dimerization of RO₂,²² and multigenerational oxidation,^23,24 have recently been proposed as efficient ways to produce these condensable organic vapors. However, the formation of OOMs in the atmosphere is expected to be an integrated result of numerous known and unknown processes, which are extremely complex and of high variability at different spatiotemporal scales. Thus, comprehensive field investigations are warranted to elucidate the origins, formation, and compositions of OOMs in diverse ambient environments.

In general, the concentration of atmospheric OOMs is extremely low (dozens ppqv to dozens pptv),²⁵ making it difficult to detect. This leads to a scarcity of global observations of OOMs. Ambient OOM measurements were initially conducted in clean environments, such as forested or remote areas,^26–29 and later sporadically in anthropogenically polluted regions.^10,30,31 Moreover, many studies have focused on evaluating the contribution of OOMs to new particle formation (NPF) and SOA,^26,32,33 whereas only few studies have specifically investigated OOM sources. Ozonolysis and OH-initiated oxidation of monoterpenes are considered to be the main sources of OOMs in the boreal forest.^34,35 Isoprene and monoterpenes are identified as the main precursors of OOMs in the Southeastern US forest, and their oxidations are moderately influenced by anthropogenic emissions.³⁶ Instead, OOMs are found to be dominantly generated from the oxidation processes of anthropogenic VOCs under the strong perturbation of nitrogen oxides (NO_x) in urban cluster areas of eastern China.^37,38 These limited observations have significantly improved our understanding of OOMs, but the properties and formation of OOMs in the polluted atmosphere are not sufficiently addressed and are the focus of this study.

The Yangtze River Delta (YRD) region in eastern China, as a global hotspot for anthropogenic emissions, suffers from severe air pollution.^39,40 Although air pollution has been dramatically mitigated in recent years,^41,42 fine particulate matter (PM_2.5) and ozone (O₃) pollution remain major challenges for continuously improving air quality in this region.^43–45 Many studies have aimed to elucidate the scientific fundamentals behind the coordinated control of these two pollutants from the perspective of precursors (NO_x and VOCs). It is noteworthy that OOMs are involved in chemical processes, resulting in PM_2.5 and O₃ pollution. Generally, VOCs are oxidized to produce RO₂, which convert NO to NO₂ and subsequently produce O₃ by NO₂ photolysis, meanwhile, RO₂ is terminated to form OOMs and then accumulate SOA by gas-particle partitioning.

In this study, we report a comprehensive analysis to ascertain the formation of OOMs during winter in Nanjing, a megacity in the YRD region. OOMs were observed using a chemical ionization atmospheric pressure interface time-of-flight mass spectrometer with nitrate reagent ions (nitrate CI-APi-TOF).¹² The characteristics of OOM sources or processes were explored by performing positive matrix factorization (PMF) on binned mass spectrometry data.^46,47 Then, the concentration, molecular composition, and volatility of the OOMs were investigated in detail. Finally, the connections of OOM formation with PM_2.5 and O₃ were discussed prospectively.

2 Methodology

2.1 Study site

The measurement was conducted at the Station for Observing Regional Processes of the Earth System (SORPES; 32°07′14′′ N, 118°57′10′′ E; 62 m a.s.l.)⁴⁸ from November 28, 2020 to January 3, 2021. The SORPES station is located in the northeastern suburbs of Nanjing, a megacity in the YRD region of eastern China. The station captures urban-scale emission activity⁴⁹ and is frequently impacted by polluted air masses from the North China Plain and the YRD urban agglomeration.^40,50 Detailed descriptions of the station can be found in previous studies.^51–55

2.2 Instrumentation

A chemical ionization atmospheric pressure interface time-of-flight mass spectrometer with nitrate reagent ions (nitrate CI-APi-TOF; Aerodyne Research Inc. and Tofwerk AG) was used to detect ambient sulfuric acid and OOMs. The working principle^2,13 and sampling configuration³⁷ of this instrument were described in previous studies. Because standards for OOM measurable by the nitrate CI-APi-TOF are yet to be established, the concentrations of OOMs were quantified by an empirical method as described below:^15,16,56Here, [OOM_i] is the concentration (molecules per cm³) of an individual OOM. On the right-hand side of the equation, first, the numerator in parentheses is the detected total signals of an OOM charged in adduct-forming or deprotonated ways, and the denominator is the sum of all nitrate ion signals; both are in the unit of ions per s. Second, C is an H₂SO₄-based calibration factor, determined as 6.0 × 10⁹ molecules per cm³ following the method of Kuerten et al..⁵⁷ Third, T_i is a mass-dependent transmission efficiency inferred by depleting reagent ions with several perfluorinated acids.⁵⁸ Although calibration using this method leads to a lower limit estimate for the concentration of OOMs, especially for those with fewer oxygen atoms,^8,16 it is currently the most feasible method for quantifying the full spectrum of OOMs, and the uncertainty in this quantification does not subvert our conclusions.

VOCs were detected by applying a proton transfer reaction time-of-flight mass spectrometer (PTR-TOF-MS, Ionicon Analytik). PM_2.5 was measured using a combined technique of light scattering photometry and beta radiation attenuation (Thermo Scientific SHARP Monitor Model 5030). The chemical compositions of PM_2.5 were obtained from a time-of-flight aerosol chemical speciation monitor (TOF-ACSM, Aerodyne Research Inc.). The number of concentrations of particles was measured using a differential mobility particle spectrometer (DMPS), covering a size range from 6 to 800 nm. Trace gases, including NO_x, NO_y, O₃, SO₂ and CO, were monitored by applying Thermo Environmental Instruments (Models 42i-TL, 42i-Y, 49i, 43i-TLE, and API T300, respectively). J(O¹D) was measured using an ultra-fast CCD detector spectrometer, UVB enhanced (Meteorologieconsult Gmbh, Germany). Meteorological parameters were recorded by the Automatic Weather Station (CAMPEEL Co., AG1000).

2.3 BinPMF analysis

Positive matrix factorization (PMF)⁵⁹ was applied to binned mass spectra (binPMF⁴⁶) to separate various sources or processes related to OOMs. Briefly, the raw mass spectra were divided into narrow bins with a width of 0.006 Th after mass calibration. Then, the PMF model inputs, including data and error matrices, were prepared based on an idea from Zhang et al.⁴⁶ The binPMF can separate the complex overlapping peaks and retain high resolution (HR) information as much as possible. This can minimize the uncertainty of HR peak fitting affecting the interpretation of PMF solutions. The PMF analysis in this study uses the IGOR-based analyzing interface SoFi (solution finder, version 6.8) and ME-2.⁶⁰ Details of the preparation and diagnostics of binPMF are provided in Section S2 in the ESI.†

3 Results and discussions

The observations were conducted during winter (low temperature and low radiation, as shown in Fig. S1† and 1a, respectively) with intensive anthropogenic emissions and their resulting aerosol pollution (Fig. S1† and 1b). The OOMs unambiguously exhibited time-dependent mass spectra and concentration differences (Fig. S1†). To deconvolute the complex dynamic processes of OOM formation, we performed a binPMF analysis and found that the 13-factor solution could explain the data variation (Fig. S5 and S6†). The selected solution includes 3 factors from the oxidation of a single anthropogenic VOC family (Fig. 1c), 2 factors related to ozone chemistry (Fig. 1c), 2 factors derived from mixed precursors with unclear processes (Fig. S14†), 4 factors dominated by nitrated phenols (NPs, Fig. S17†) and 2 factors dominated by fluorinated contaminations. NPs that are usually volatile have been broadly investigated.^61–64 Fluorinated contaminations come from Teflon tube volatiles and perfluoric acid for transmission efficiency calibrations. These two types of compounds are not our concern. The other 7 factors are dominated by organic nitrates (Fig. 2 and S14†), which are expected to contribute significantly to the particulate organic nitrates observed at this site.⁶⁵ Detailed discussions of these OOM factors are given below (Table 1).

Fig. 1 Median diurnal variations of main compounds and parameters. (a) NO, NO₂, O₃, and PM_2.5. (b) J(O¹D) and temperature. (c) The Arom-OOM, Aliph-OOM-I, Aliph-OOM-II, O₃-related-I, and O₃-related-II factors from binPMF analysis to OOMs.

Fig. 2 Profiles of 5 binPMF factors. Mass spectra of (a) the Arom-OOM factor, (b) the Aliph-OOM-I factor, (c) the Aliph-OOM-II factor, (d) the O₃-related-I factor, and (e) the O₃-related-II factor. The elemental formulae of the major peaks are labeled above them. Peaks are color-coded by n_N, and the fractions of peaks grouped by n_N are reported in the pie chart for each factor. The gray sticks are fluorinated contaminations or non-identified compounds. The nitrated phenols are drawn separately with black peaks. Therefore, n_N can more reliably represent the number of nitrate groups in each molecule.

Table 1 Summary of molecular characteristics of 7 discussed non-nitrated-phenol factors. The calculation of the relevant parameters is given in Section S3 in the ESI. The major peaks of each factor are summarized in Section S4 in the ESI^a

Factor	Average concentration (cm^−3)	Effective formulas	MW (g mol^−1)	OSc	O : C	N : C	DBE	log10(C*(μg m^−3)) in 300 K
a MW is the molecular weight, OSc is the carbon oxidation state, O : C is the oxygen to carbon ratio, N : C is the nitrogen to carbon ratio, DBE is the double bond equivalent, C* the saturation concentration and log10(C*) is the volatility.
Arom-OOM	6.70 × 10^6	C8.4H13.4O6.1N1.0	226.0	−0.68	0.78	0.13	2.2	0.9
Aliph-OOM I	7.02 × 10^6	C8.2H13.8O6.2N1.2	228.3	−0.79	0.84	0.16	1.6	1.2
Aliph-OOM II	8.00 × 10^6	C7.4H13.1O6.9N1.7	235.4	−1.02	1.00	0.25	1.0	1.4
O3-related I	8.01 × 10^6	C7.6H11.9O7.0N1.2	232.5	−0.40	0.99	0.17	2.1	0.5
O3-related II	7.17 × 10^6	C7.0H10.4O6.1N0.9	205.4	−0.29	0.94	0.14	2.4	1.6
MT-mixed-OOM	6.19 × 10^6	C8.4H13.4O5.7N1.0	219.6	−0.77	0.74	0.13	2.2	1.3
Mixed-OOM	5.65 × 10^6	C7.4H11.2O5.8N0.9	205.6	−0.51	0.86	0.14	2.4	1.8

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3.1 Anthropogenic VOC chemistry

The first three factors possess clear anthropogenic precursor features, including one mainly from the oxidation of aromatic VOCs (denoted as Arom-OOM) and the other two from the oxidation of aliphatic VOCs (Aliph-OOMs I and II). The Arom-OOM factor is characterized by molecules with a double bond equivalent (DBE) of 3 (Fig. 2a), in which the most prominent ones are C_xH_2x−5O₆N (x = [6, 12], Table S2†). They are produced from the reactions of a homologous series of OH-initiated aromatic bicyclic peroxy radicals with NO.⁶⁶ C₈-OOMs are the most abundant in this factor (Fig. 3a), which coincides with the OH reactivity distribution of aromatics (Fig. S8a†). This factor has a positive correlation (Fig. 4) and similar daily variation (Fig. S8b†) with the proxies of aromatic photo-oxidation (aromatics × J(O¹D)), with its concentration reaching a peak plateau after 10:00 local time (LT), declining after 14:00 LT, and staying low throughout the night (Fig. 1c). The C_xH_2x−5O₈N (x = [7, 11]) series (Table S2†) potentially formed through autoxidation (Fig. S9†) is still easy to observe although the abundances of NO_x measured here are significantly higher than the set conditions of previous laboratory studies.^67–69 In addition, products with DBE < 3 (Fig. 3b) in this factor are supposed to be produced by multigenerational OH oxidations. These pathways can efficiently make aromatic-derived OOMs more oxidized, but more studies are needed to clarify their persistence under such heavily polluted conditions.

Fig. 3 The chemical distributions of 5 binPMF factors. The observed non-nitro OOMs grouped by (a) the number of carbon atoms (n_C), (b) DBE, and (c) the number of effective oxygen atoms (n_Oeff = n_O − 2 × n_N), which exclude –NO₂ from the nitrate moiety.

Fig. 4 Correlations of binPMF factors with external gas-phase and particulate tracers. The colors are differentiated by Pearson correlation coefficients. Note: O_x is the total oxidants (O_x = O₃ + NO₂ + NO_z and NO_z = NO_y − NO_x); aromatics × J(O¹D) are the proxies of aromatic photo-oxidation; and primary and secondary organic aerosols (POA and SOA) are derived from PMF analysis of the organic aerosol detected by TOF-ACSM.

Unlike the Arom-OOM factor, the two factors from aliphatic oxidation comprise more saturated compounds (Fig. 1b, c and 3b), particularly a series of multi-nitrates (Tables S3 and S4†), such as C_xH_2x−2O₇₋₈N₂ (x = [5, 13]) and C_xH_2xO₇N₂ (x = [4, 13]). In the case of alkane oxidation under high NO_x, one OH attack can only add one nitrate group or one carbonyl group to the product molecule (Fig. S10†). According to the method proposed by Liu et al.,³⁷ the two Aliph-OOM factors are dominated by second- and third-generation products (Fig. S10†). This observation validates the substantial amount of aliphatic dinitrates and trinitrates measured in recent laboratory experiments.^70,71 It seems that aromatic-derived OOMs contain more oxygen atoms than aliphatic-derived OOMs (Fig. 3c), and the latter are more prone to contain nitrate groups than the former (Fig. 1a–c). Thus, we speculate that aliphatics and aromatics play distinct roles in the budgets of reactive nitrogen oxides.⁷²

Both Aliph-OOM factors are correlated with PM_2.5 (Fig. 4), suggesting their close connections with aerosol pollution. However, the two Aliph-OOM factors differ obviously in their temporal variation. The Aliph-OOM I factor has a later daytime peak (about 13:00–18:00 LT, Fig. 1c), suggesting that these multi-generational products are formed locally and require enough photochemistry. In contrast, the Aliph-OOM-II factor shows unclear diurnal variation (Fig. 1c) and presents many accumulation episodes in the time series, such as PM_2.5 (Fig. S1†). Thus, it is more likely to characterize OOMs in aged air masses transported to this site. The properties of OOMs from the two different processes described above are distinct. The Aliph-OOM-I factor has a larger proportion of heavy (C_10–14) molecules than the Aliph-OOM-II factor does (Fig. 3a), which is probably because long-chain aliphatic nitrates are less volatile and more easily consumed by condensation onto particle surfaces during transport. Moreover, the Aliph-OOM-I factor has a higher fraction of potential carbonyl groups (Fig. 3b), such as the C_xH_2x−3O₆N (x = [5, 13]) series with a DBE of 2, while the Aliph-OOM-II factor has a higher proportion of nitrate groups (Fig. 2b and c), such as the C_xH_2x−1O₉₋₁₀N₃ (x = [5, 10]) series. Both carbonyl and nitrate moieties are vulnerable to loss through heterogeneous uptake on particles.^72,73 The difference in chemical composition between the two factors and their high concentration at high particle loadings may be attributed to their generation processes. Future laboratory studies are urgently needed to reveal the unknown part of aliphatic oxidation in a typical urban atmosphere.

3.2 Ozone-related chemistry

In contrast to the above factors distinguished by precursors, the following two factors are driven by photochemistry. The O₃-related I factor is well correlated with ozone and peroxyacetyl nitrate (PAN) in 17 ozone production cases (Fig. 5a and b). These cases are selected by the following criteria: (a) good correlation between O₃ and time (r > 0.9), i.e., O₃ is continuously produced without substantial interruptions; (b) the maximum hourly J(O¹D) for the day exceeds 1 × 10⁻⁵ s⁻¹; and (c) the duration of the case exceeds 2 hours. It follows that this factor exhibiting significant daytime peaks (Fig. 1c) is likely produced jointly with ozone and PAN by tropospheric photochemistry involving VOCs and NO_x.⁷⁴ The fingerprint molecules of the O₃-related-I factor (Fig. 2d and Table S5†) are the C_xH_2x−3O₆N (x = [4, 12]) and C_xH_2x−1O₆N (x = [4, 11]) series, which presumably contain a peroxy-acyl-nitrate moiety but one more carbonyl or hydroxyl than PAN, respectively. The O₃-related I factor has the lowest volatility (Table 1), resulting from the outstanding proportion of OOMs with an effective oxygen number (n_Oeff = n_O − 2 × n_N) over 4 (Fig. 3c). This indicates that this specific VOC oxidation process linked to ozone production facilitates the production of condensable organic vapors and, hence, the accumulation of SOA (Fig. S12†).

Fig. 5 Co-generation of the two O₃-related factors with ozone. Scatter plots of the two O₃-related factors with (a) ozone and (b) PAN in 17 ozone production cases. (c) Correlation between the increase in the two O₃-related factors and ozone. In 17 cases. Error bars indicate the statistical (1σ) uncertainties in fitting the ozone increase, and OOM increases during each case. All circles are colored by datetime to separate individual cases.

The O₃-related II factor, which is dominated by the C_xH_2x−3O₆N (x = [4, 10]) and C_xH_2x−1O₆N (x = [4, 9]) series (Fig. 2e and Table S6†), is moderately correlated with ozone and weakly correlated with PAN (Fig. 5a and b). This shows that the O₃-related II factor is partially homologous to the O₃-related-I factor. Both aliphatic-derived (DBE = 0, 1) and aromatic-derived OOMs (DBE = 3, 4) are present in these two factors (Fig. 3b), illustrating the crucial effect of anthropogenic VOCs on ozone production. Compared with the O₃-related-I factor, the O₃-related-II factor has a lower concentration in the morning (high NO) and a higher concentration in the afternoon (high temperature). Importantly, the O₃-related-II factor contains the most non-nitrates, which are related to chemical processes influenced by lower NO and higher temperature. It could be that the branching ratio of the RO₂ + NO reaction to nitrate decreases as the temperature increases,⁷² or perhaps the contribution of the RO₂ + HO₂ reaction increases as NO decreases and temperature increases.³⁷

3.3 Other OOM factors

Here are two OOM factors of mixed precursor origin without distinctive features. The MT-mixed-OOM factor contains potential monoterpene-derived OOMs (Fig. S14a†), such as C₁₀H_15,17O_xN (x = [5, 8]) and C₁₀H₁₆O_xN₂ (x = [7, 10]). Monoterpenes are likely to stem from anthropogenic emissions in urban areas during the cold season,⁷⁵ and thus the co-presence of many oxidation products of anthropogenic precursors in this factor is understandable. The mixed-OOM factor comprising aliphatic-derived and aromatic-derived OOMs (Fig. S14b†) shows no clear relationship with the external gas-phase and particulate tracers (Fig. 4). It is noteworthy that these mixed factors cannot be further split by increasing the number of factors (Fig. S15 and S16†), indicating that they do not suffer from incomplete separations. Instead, they may come from complex nonlinear formation processes that are real in the atmosphere but cannot be interpreted well based on current understandings.

3.4 Connections of OOMs with PM_2.5 and O₃

Using binPMF to separate overlapping peaks and provide useful chemical information, over 1500 non-nitro molecules were identified through HR fitting and then reconstructed from the selected binPMF solution (Fig. S18a†). The mean total concentration is 4.7 × 10⁷ molecules per cm³, of which about 81% is organic nitrate generated by the reaction of NO_x with RO₂ from anthropogenic-VOC oxidations (Fig. S18a†). Under such a strong influence of NO_x, non-nitro OOMs can still acquire 3–7 effective oxygen atoms (even over 7 for a few molecules) (Fig. S18b†), which benefit from multigenerational oxidation and autoxidation discussed in the aforementioned binPMF factors. Interestingly, the total OOM concentration is found to be correlated with PM_2.5 and O₃ (Fig. S19†). Understanding the formation of OOMs in relation to PM_2.5 and O₃ is an intriguing issue in the context of VOCs acting as fuels for atmospheric chemistry.⁷⁶

First, the observed concentrations of OOMs from ELVOC to SVOC show unexpected upward trends with the accumulation of PM_2.5 (Fig. 6a). However, this suggests that OOM condensation (roughly represented by OOMs × CS, Fig. 6b) remains a crucial pathway of SOA formation during haze when the multiphase reactions are proposed to be significant.^2,73,77 This efficient gas-to-phase conversion has been revealed to be prevalent in major urban cluster areas in eastern China under highly polluted atmospheric conditions.¹⁰ It is noteworthy that the percentage of SVOC in OOMs increases with PM_2.5 whereas the fractions of ELVOC and LVOC decrease (Fig. 6a), which demonstrates that less volatile OOMs are more susceptible to condensation loss. However, the source of OOMs is supposed to increase much faster and outperforms the enhanced condensational loss of OOMs. With the buildup of haze, the emitted precursors (e.g., aromatics) are enriched (Fig. 6c) owing to stagnant wind fields coupled with a shallow boundary layer.^78,79 At the high OH consumption rate induced by these reactive gases, the abundance of OH (represented by the OH proxy,⁸⁰) does not decline (Fig. 6c) most likely owing to the rapid OH recycling from peroxyl radicals⁸¹ and the atmospheric oxidation capability amplified by heterogeneous reactions on aerosol surfaces.^49,82,83 The intense photochemistry can also be deduced from the co-accumulation of PAN and O_x with PM_2.5 (Fig. S20†). Consequently, the formation of OOMs and the contribution of OOMs to SOA are enhanced during haze (Fig. 6b).

Fig. 6 The enhanced formation of OOMs during the haze (daytime). (a) Boxplots of the concentrations of OOMs (ELVOC, LVOC, and SVOC) binned by PM_2.5 in each 30 μg m⁻³ interval of PM_2.5. All data for PM_2.5 > 180 μg m⁻³ are represented by dashed box plots owing to too few data points. The relative contributions of ELVOC, LVOC, and SVOC for different PM_2.5 levels are displayed as color-filled areas. (b) Condensation sink (CS) and OOMs × CS roughly represent SOA production rate by OOM condensation, depending on PM_2.5. (c) Aromatics and OH proxy are accumulated with the increase of PM_2.5. All solid lines in (b) and (c) are obtained from the least squares linear fit, shaded with a 90% confidence interval.

Further, such strong photochemical production of OOMs is accompanied by efficient ozone production, which is usually masked by the fast removal caused by heavily emitted NO.⁸¹ As shown in Fig. 7a, under moderate radiation conditions (the maximum daily J(O¹D) > 1 × 10⁻⁵ s⁻¹), the maximum daily 8 h average (MDA8) ozone follows 24 h average PM_2.5 and is elevated even on haze days. It has recently been found that ozone can benefit from active photochemistry to exceed the air quality standard during cold seasons in some areas with high VOC emissions^84,85 although ozone is generally considered to be a summertime pollutant.⁸⁶ Here, we pick three regimes on the scatter plot of MDA8 O₃ and 24 h average PM_2.5 (Fig. 7a) and then compare the formation of OOMs in different regimes (Fig. 7b). Under relatively clean conditions (regime 1: low 24 h average PM_2.5 and mid MDA8 O₃), OOMs with different volatilities are mainly assigned to ozone-related factors (Fig. 7b). When shifting to normal winter haze conditions (regime 2: high 24 h average PM_2.5 and low MDA8 O₃), the major sources of OOMs are more extensive with clearly increased contributions from the two Aliph-OOM factors and the Arom-OOM factor (Fig. 7b), which ultimately increases OOM concentrations (Fig. 7b). The highest concentrations of OOMs are present in regime 3 (high 24 h average PM_2.5 and high MDA8 O₃) where OOMs are mainly sourced from ozone-related factors, followed by the Aliph-OOM factors (Fig. 7b). The role of VOC in PM_2.5 and O₃ pollution is usually interpreted based on traditional VOC oxidation mechanisms,^81,85 our analysis indicates that the perturbations introduced by the yet-to-be-resolved part of VOC oxidation (i.e., formation of OOMs and organic nitrate) need to be addressed.

Fig. 7 The concurrence of OOMs with PM_2.5 and ozone. (a) Scatter plot of MDA8 O₃ with 24 h averaged PM_2.5. Each dot is colored by the maximum hourly J(O¹D) of the corresponding day. Based on this chart, 3 regimes, including regime 1 (low 24 h average PM_2.5 and mid MDA8 O₃), regime 2 (high 24 h average PM_2.5 and low MDA8 O₃), and regime 3 (high 24 h average PM_2.5 and high MDA8 O₃), are determined. The light red solid line is obtained from the least squares linear fit in the case of J(O¹D) > 1 × 10⁻⁵ s⁻¹, and the light blue solid line is obtained in the case of J(O¹D) < 0.8 × 10⁻⁵ s⁻¹. (b) The contributions of binPMF factors to OOMs (ELVOC, LVOC, and SVOC) in all-time average and in 3 regimes. The total OOM concentration in different cases is given by solid black diamonds.

4 Summary and conclusions

We investigated the formation of gas-phase OOMs observed using a nitrate CI-APi-TOF in a megacity of eastern China during the winter. We performed binPMF analysis on the raw spectra. A high-quality OOM dataset containing over 1500 OOM molecules was established using binPMF to separate overlapping peaks. After excluding nitrated phenols, these OOMs have a mean total concentration of 4.7 × 10⁷ molecules per cm³, which predominantly comprised organic nitrate (∼81% of the total), revealing the intense impact of NO_x on the OOM formation. In addition, most OOMs contain 3 to 7 effective oxygen atoms owing to multigenerational oxidation and autoxidation, and their low-volatility feature favors SOA formation.

The binPMF analysis also identified 7 factors characterizing anthropogenic OOMs (excluding NPs). All factors mainly comprise homologous compounds because their precursors, anthropogenic VOCs, are usually co-emitted. Specifically, the Arom-OOM factor (peaking at 10:00–14:00 LT) is characterized by aromatic-derived unsaturated mononitrates, such as C_xH_2x−5O₆₋₈N (x = [6, 11]). The Aliph-OOM-I factor (peaking at 13:00 to 18:00 LT) is dominated by aliphatic-derived nearly and fully saturated organic nitrates (mononitrates are the most abundant), such as C_xH_2x−1O_5,6N (x = [4, 12]), C_xH_2xO₇N₂ (x = [4, 14]) and C_xH_2x−2O_7,8N₂ (x = [6, 13]). The Aliph-OOM-II factor, markedly affected by transport and associated with haze accumulation, comprises aliphatic-derived saturated and near-saturated organic nitrates (dinitrates are the most abundant), such as C_xH_2xO₇N₂ (x = [4, 13]), C_xH_2x−2O_7,8N₂ (x = [5, 13]), and C_xH_2x−1O_9,10N₃ (x = [5, 10]). The O₃-related-I factor (peaking around 13:00 LT), whose fingerprint molecules are C_xH_2x−3O₆N (x = [4, 12]), is correlated with ozone and PAN; hence, it is suggested to be an important co-products with ozone from atmospheric photochemistry. The O₃-related-II factor (peaking around 13:00 LT) also correlates with ozone. In addition to sharing the same fingerprint molecules with the O₃-related-I factor, it contains the most abundant non-nitrates, such as C_xH_2x−4O_4,5 (x = [5, 10]), possibly derived from RO₂ terminations influenced by lower NO and higher temperature. The MT-mixed-OOM factor and the Mixed-OOM factor are derived from mixed precursors undergoing unknown processes. Notably, these characteristic profiles of OOMs have not been found in the available laboratory results and cannot be well explained by existing explicit chemical mechanisms. These observational findings can inform and inspire future laboratory and mechanistic studies of OOMs.

Finally, we analyzed the relationship of OOMs with PM_2.5 and O₃. As the condensation sink increases during the buildup of haze, the concentration of OOMs from ELVOC to SVOC shows an unexpected upward trend. This phenomenon illustrates that the VOC to SOA process is accelerated through OOM condensation and indicates the enhanced photochemical production of OOMs, which is powered by the accumulated precursors owing to limited air diffusion and sustained oxidants by rapid HO_x (OH + HO₂) cycling and heterogeneous reactions. Moreover, the highest OOM concentrations occurred in the case of the co-enhancement of PM_2.5 and O₃, which is generally due to active photochemistry on haze days. In detail, this is presumably ascribed to the chemical processes characterized by ozone-related factors that boost both O₃ and low-volatility OOMs, as well as those represented by the Aliph-OOM factors that are tightly related to PM_2.5. More studies should be conducted to unravel the formation of OOMs and to complement the understanding of the role of VOC oxidation in PM_2.5 and ozone pollution from this perspective.

Author contributions

AD, WN and Yuliang Liu designed the study. Yuliang Liu, CL, WN and CY analyzed the data. YL, CL and WN wrote the manuscript. Yuanyuan Li, DG, LC, CZ, LW, YZ, TL, XQ, JW and XC collected other research materials. All authors participated in the relevant scientific discussion and commented on the manuscript.

Conflicts of interest

There are no conflicts to declare.

Acknowledgements

We thank the tofTools team for providing programs for data analysis of mass spectrometry. This work was supported by the National Natural Science Foundation of China (NSFC) project (92044301, 42220104006, 41875175, 42075101 and 41975154), the Jiangsu Provincial Collaborative Innovation Center of Climate Change and the Fundamental Research Funds for the Central Universities.

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Footnotes

† Electronic supplementary information (ESI) available. See DOI: https://doi.org/10.1039/d2ea00143h

‡ These authors contributed equally to this work.

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